An Experimental Evaluation of Pore Plugging and Permeability Reduction Near SAGD Sand Control Liners
Bibliographic record
Abstract
Abstract This paper presents the results of an experimental investigation to determine the mechanisms of pore plugging and permeability reduction near SAGD screen liners. The aim is to arrive at a liner design that maximizes wellbore productivity without compromising the sand control function of the liner. We set up a large-scale Sand Retention Testing (SRT) facility that accommodates a multi-slot liner coupon at the base of a sand-pack with representative grain shape and particle size distribution (PSD) of typical oil sands. Brine is injected at different flow rates and pressure differences across the coupon and the sand-pack as well as the mass and PSD of the produced sand and fines are measured during the test. Further, the PSD and concentration of migrated fines (<44 microns) along the sand-pack are determined in a post-mortem analysis. The testing results are used to assess the effect of slot size and slot density on the sand control performance as well as pore-plugging and permeability alterations near the sand-control liner. We observed that the slot size, slot density and flow rate highly affect the concentration and PSD of produced fines as well as accumulated fines (pore clogging) above the screen. For the same flow rates and total injected pore volume, wider screen aperture and higher slot density result in lower fines accumulation above the screen but more sanding. Further, the variation of slot density alters the flow convergence behind the slots, hence, the size and concentration of mobilized fines. Results indicate that higher fines concentration near the screen reduces the retained permeability, hence, lowers the wellbore productivity. This paper provides a new insight into pore plugging and fines migration adjacent the sand control liner. It also introduces a new testing method to optimize the design of sand control liners for minimum productivity impairment in SAGD projects.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".